Data and feature strategy
Location page: Cologne
Custom ML Development for Companies Cologne
Development, training and integration of machine learning models for prediction, classification and intelligent product features.
Cologne blends media, communications and mid-market businesses with fast campaign and content cycles.
Request ML projectML from data to deployment
I build ML pipelines from data preparation and feature engineering to model training, evaluation and production deployment. Example implementations include an AI Real Voice TTS for Voicfy based on a diffusion model and a news-gathering trading system that performs stock-level fundamental analysis.
Model training, evaluation and iteration including diffusion models for audio/TTS
Deployment, monitoring and MLOps setup for production ML and analytics systems
Cologne market context
Industry focus
- - Media & communications
- - Mid-market businesses
- - Brand-led services
Local leverage points
- - Content automation
- - Lead qualification
- - Cross-channel workflows
FAQ
When do you need a custom ML model?
When off-the-shelf models do not provide the required accuracy, latency or domain fit for your use case.
Can a model be integrated into existing systems?
Yes. Integration is possible via APIs, batch pipelines or direct product features, including monitoring in production.
Do you have practical ML examples from your work?
Yes. This includes an AI Real Voice TTS for Voicfy based on a diffusion model and a news-gathering trading platform with per-stock fundamental analysis.
Can AI concretely reduce workload for marketing teams in Cologne?
Yes, especially in research, briefing, variant generation and qualification.
Are short pilot projects feasible for mid-market teams?
Yes, with tightly scoped use cases and measurable KPI targets.
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Share your goal, timeline and budget for Cologne. You will get a clear recommendation for the next step.